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Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm
Thyroid cancer (TC) is known with a high rate of persistence and recurrence. We aimed to develop a prognostic signature to monitor and assess the survival of TC patients. mRNA expression and methylation data were downloaded from the TCGA database. Then, R package methylmix was applied to construct a...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8436924/ https://www.ncbi.nlm.nih.gov/pubmed/34456184 http://dx.doi.org/10.18632/aging.203338 |
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author | Chen, Zhiwei Liu, Xiaoli Liu, Fangfang Zhang, Guolie Tu, Haijian Lin, Wei Lin, Haifeng |
author_facet | Chen, Zhiwei Liu, Xiaoli Liu, Fangfang Zhang, Guolie Tu, Haijian Lin, Wei Lin, Haifeng |
author_sort | Chen, Zhiwei |
collection | PubMed |
description | Thyroid cancer (TC) is known with a high rate of persistence and recurrence. We aimed to develop a prognostic signature to monitor and assess the survival of TC patients. mRNA expression and methylation data were downloaded from the TCGA database. Then, R package methylmix was applied to construct a mixed model was used to identify methylation-driven genes (MDGs) according to the methylation levels. Furthermore, an MDGs based prognostic signature and predictive nomogram were constructed according to the analysis of univariate and multivariate Cox regression. Totally 62 methylation-driven genes that were mainly enriched in substrate-dependent cell migration, cellular response to mechanical stimulus, et al. were found in TC tissues. aldolase C (AldoC), C14orf62, dishevelled 1 (DVL1), and protein tyrosine phosphatase receptor type C (PTPRC) were identified to be significantly related to patients' survival, and may serve as independent prognostic biomarkers for TC. Additionally, the prognostic methylation signature and a novel prognostic, predictive nomogram was established based on the methylation level of 4 MDGs. In this study, we developed a 4-MDGs based prognostic model, which might be the potential predictors for the survival rate of TC patients, and this findings might provide a novel sight for accurate monitoring and prognosis assessment. |
format | Online Article Text |
id | pubmed-8436924 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-84369242021-09-14 Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm Chen, Zhiwei Liu, Xiaoli Liu, Fangfang Zhang, Guolie Tu, Haijian Lin, Wei Lin, Haifeng Aging (Albany NY) Research Paper Thyroid cancer (TC) is known with a high rate of persistence and recurrence. We aimed to develop a prognostic signature to monitor and assess the survival of TC patients. mRNA expression and methylation data were downloaded from the TCGA database. Then, R package methylmix was applied to construct a mixed model was used to identify methylation-driven genes (MDGs) according to the methylation levels. Furthermore, an MDGs based prognostic signature and predictive nomogram were constructed according to the analysis of univariate and multivariate Cox regression. Totally 62 methylation-driven genes that were mainly enriched in substrate-dependent cell migration, cellular response to mechanical stimulus, et al. were found in TC tissues. aldolase C (AldoC), C14orf62, dishevelled 1 (DVL1), and protein tyrosine phosphatase receptor type C (PTPRC) were identified to be significantly related to patients' survival, and may serve as independent prognostic biomarkers for TC. Additionally, the prognostic methylation signature and a novel prognostic, predictive nomogram was established based on the methylation level of 4 MDGs. In this study, we developed a 4-MDGs based prognostic model, which might be the potential predictors for the survival rate of TC patients, and this findings might provide a novel sight for accurate monitoring and prognosis assessment. Impact Journals 2021-08-29 /pmc/articles/PMC8436924/ /pubmed/34456184 http://dx.doi.org/10.18632/aging.203338 Text en Copyright: © 2021 Chen et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Chen, Zhiwei Liu, Xiaoli Liu, Fangfang Zhang, Guolie Tu, Haijian Lin, Wei Lin, Haifeng Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm |
title | Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm |
title_full | Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm |
title_fullStr | Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm |
title_full_unstemmed | Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm |
title_short | Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm |
title_sort | identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8436924/ https://www.ncbi.nlm.nih.gov/pubmed/34456184 http://dx.doi.org/10.18632/aging.203338 |
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